understand-diff
# ClaudeWave: understand-diff The understand-diff skill analyzes git diffs and pull requests by cross-referencing changed files against a project's knowledge graph to identify affected components, dependency chains, and potential risks. Use this skill when reviewing code changes to understand what components are impacted, which services depend on modifications, and what architectural layers might be affected by the diff.
git clone --depth 1 https://github.com/Egonex-AI/Understand-Anything /tmp/understand-diff && cp -r /tmp/understand-diff/understand-anything-plugin/skills/understand-diff ~/.claude/skills/understand-diffSKILL.md
# /understand-diff
Analyze the current code changes against the knowledge graph in the project's data directory (`.ua/knowledge-graph.json`, or the legacy `.understand-anything/knowledge-graph.json` when that directory is present).
## Graph Structure Reference
The knowledge graph JSON has this structure:
- `project` — {name, description, languages, frameworks, analyzedAt, gitCommitHash}
- `nodes[]` — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}
- Code node types: file, function, class, module, concept
- Non-code node types: config, document, service, table, endpoint, pipeline, schema, resource
- Domain/knowledge node types: domain, flow, step, article, entity, topic, claim, source
- IDs use the node type as prefix, e.g. `file:path`, `function:path:name`, `config:path`, `article:path`
- `edges[]` — each has {source, target, type, direction, weight}
- Key types: imports, contains, calls, depends_on, configures, documents, deploys, triggers, contains_flow, flow_step, related, cites
- `layers[]` — each has {id, name, description, nodeIds[]}
- `tour[]` — each has {order, title, description, nodeIds[]}
## How to Read Efficiently
1. Use Grep to search within the JSON for relevant entries BEFORE reading the full file
2. Only read sections you need — don't dump the entire graph into context
3. Node names and summaries are the most useful fields for understanding
4. Edges tell you how components connect — follow imports and calls for dependency chains
## Instructions
1. **Resolve the data directory `$UA_DIR`.** Run `UA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua)` — this is the legacy `.understand-anything/` when it already exists, otherwise the new `.ua/`. Check that `$UA_DIR/knowledge-graph.json` exists. If not, tell the user to run `/understand` first.
2. **Get the changed files list** (do NOT read the graph yet):
- If on a branch with uncommitted changes: `git diff --name-only`
- If on a feature branch: `git diff main...HEAD --name-only` (or the base branch)
- If the user specifies a PR number: get the diff from that PR
3. **Read project metadata and check graph freshness** — use Grep or Read with a line limit to extract the `"project"` section, including `gitCommitHash` as `GRAPH_COMMIT_RAW`, then:
- Resolve it as a commit before using it in any Git diff. From the project root, compare the resolved commit with `git rev-parse HEAD` and inspect project-scoped committed and working-tree changes:
```bash
GRAPH_COMMIT=$(git rev-parse --verify --end-of-options "${GRAPH_COMMIT_RAW}^{commit}" 2>/dev/null)
git rev-parse HEAD
git diff --name-only "$GRAPH_COMMIT" HEAD -- .
git diff --cached --name-only -- .
git diff --name-only -- .
git ls-files --others --exclude-standard -- .
```
- The `-- .` pathspec is required: commits that only touch a sibling monorepo project must not make this graph stale. A hash mismatch alone is not stale when the project diff is empty.
- Ignore the selected data directory (`.ua/` or legacy `.understand-anything/`) in every command's output because it contains generated graph artifacts, not project source drift.
- If the committed diff or any working-tree command reports project files, warn before impact analysis that the graph may omit those changes. Suggest: Run `/understand` to refresh the graph.
- Run the commit diff only when `GRAPH_COMMIT_RAW` resolves successfully. If the graph commit or Git metadata is missing, invalid, or unavailable, give a brief best-effort warning and continue instead of blocking.
4. **Find nodes for changed files** — for each changed file path, use Grep to search the knowledge graph for:
- Nodes with matching `"filePath"` values (e.g., `grep "changed/file/path"`)
- This finds file-level nodes (including non-code types) AND function/class nodes defined in those files
- Note the `id` values of all matched nodes
5. **Find connected edges (1-hop)** — for each matched node ID, Grep for that ID in the edges to find:
- What imports or depends on the changed nodes (upstream callers)
- What the changed nodes import or call (downstream dependencies)
- These are the "affected components" — things that might break or need updating
6. **Identify affected layers** — Grep for the matched node IDs in the `"layers"` section to determine which architectural layers are touched.
7. **Provide structured analysis**:
- **Changed Components**: What was directly modified (with summaries from matched nodes)
- **Affected Components**: What might be impacted (from 1-hop edges)
- **Affected Layers**: Which architectural layers are touched and cross-layer concerns
- **Risk Assessment**: Based on node `complexity` values, number of cross-layer edges, and blast radius (number of affected components)
- Suggest what to review carefully and any potential issues
8. **Write diff overlay for dashboard** — after producing the analysis, write the diff data to `$UA_DIR/diff-overlay.json` so the dashboard can visualize changed and affected components. The file contains:
```json
{
"version": "1.0.0",
"baseBranch": "<the base branch used>",
"generatedAt": "<ISO timestamp>",
"changedFiles": ["<list of changed file paths>"],
"changedNodeIds": ["<node IDs from step 4>"],
"affectedNodeIds": ["<node IDs from step 5, excluding changedNodeIds>"]
}
```
After writing, tell the user they can run `/understand-anything:understand-dashboard` to see the diff overlay visually.Use when you need to ask questions about a codebase or understand code using a knowledge graph
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